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Disorders of the heart and blood vessels are the leading cause of health problems and death. Early detection of them is extremely valuable as it can prevent serious incidents (e.g. heart attack, stroke) and associated complications. This requires extending the typical mobile monitoring methods (e.g. Holter ECG, tele-ECG) by introduction of integrated, multiparametric solutions for continuous monitoring of the cardiovascular system. In this paper we propose the wearable system that integrates measurements of cardiac data with actual estimation of the cardiovascular risk level. It consists of two wirelessly connected devices, one designed in the form of a necklace, the another one in the form of a bracelet (wrist watch). These devices enable continuous measurement of electrocardiographic, plethysmographic (impedance-based and optical-based) and accelerometric signals. Collected signals and calculated parameters indicate the electrical and mechanical state of the heart and are processed to estimate a risk level. Depending on the risk level an appropriate alert is triggered and transmitted to predefined users (e.g. emergency departments, the family doctor, etc.).

Recently, different smart glasses solutions have been proposed on the market. The rapid development of this wearable technology has led to several research projects related to applications of smart glasses in healthcare. In this paper we propose a general architecture of the system enabling data integration for the recognized person. In the proposed system smart glasses integrates data obtained for the recognized patient from health care information systems, from devices connected to the patient and from the patient himself. The data integration is possible, if proper patient recognition procedure is used. Therefore, we evaluated three identification methods based on face recognition and using the recognition of graphical markers (i.e. QR-codes and proposed color-based codes). The results show that it is possible to obtain reliable and fast recognition results during the video acquisition by the smart glasses camera.